RecordMove

Predictive maintenance expert to computer vision engineer

A predictive maintenance expert already meets 15% of what the computer vision engineer role asks for. The move turns on 26 required skills not yet in the profile.

Fig. 1 · Skill transfer ESCO v1.2.1 · directional

From predictive maintenance expert

Distant match

To computer vision engineer

6 You already bring

26 Still to learn

52 Skills in the target role2

Learning distance A rebuild

86.6/ 100

adjacentmoderatesubstantialcareer change

1 How much of what a computer vision engineer is expected to do is already part of a predictive maintenance expert’s work. Directional: the figure for the reverse move differs, because moving into a speciality is not the same problem as moving out of one. 2 Every skill the computer vision engineer role is recorded as needing, required and optional together. What these numbers mean.

Why

Why this move works

A computer vision engineer role treats 6 of its required skills as things a predictive maintenance expert already does. You would walk in with these on day one.

apply statistical analysis techniques
computer programming
computer simulation
deliver visual presentation of data
develop data processing applications
statistics

What stands in the way is 26 required skills the profile does not yet cover. Table 3 groups them; Table 4 says which to take first.

Table 2

Table 2 · What you already bring

Of the 6 skills that carry over, these are the ones fewest other occupations ask for. A computer vision engineer role needs them, and most people applying for one will not have them already. This is the part of a predictive maintenance expert background worth leading with.

Skill the target role also needs Area

already held develop data processing applications working with computers
already held deliver visual presentation of data communication, collaboration and creativity
already held computer simulation information and communication technologies (icts)
already held computer programming information and communication technologies (icts)
already held apply statistical analysis techniques information skills
already held statistics natural sciences, mathematics and statistics

All 6 carried skills, including the 6 the computer vision engineer role treats as required.

Table 3

Table 3 · What you may need to learn

The 46 missing skills fall into 8 areas of the ESCO skill hierarchy, numbered in the order worth working in. Areas carrying the most required skills come first, and inside each one the required skills sit above the optional ones. Nothing here is a verdict on you: it is a list of what this particular job asks for that your current one does not.

Skill to pick up Tier

01 information and communication technologies (icts) 9 required, 7 supplementary

still to learn Python (computer programming) required
still to learn digital twin technology required
still to learn integrated development environment software required
still to learn principles of artificial intelligence required
still to learn data engineering required
still to learn data science required
still to learn image recognition required
still to learn machine learning required
still to learn scientific computing required

optional, not held cognitive computing optional
optional, not held quantum computing optional
optional, not held query languages optional
optional, not held resource description framework query language optional
optional, not held computer graphics optional
optional, not held deep learning optional
optional, not held digital systems optional

02 working with computers 9 required, 3 supplementary

still to learn develop software prototype required
still to learn establish data processes required
still to learn normalise data required
still to learn use software libraries required
still to learn utilise computer-aided software engineering tools required
still to learn develop computer vision system required
still to learn implement data quality processes required
still to learn perform data cleansing required
still to learn perform dimensionality reduction required

optional, not held debug software optional
optional, not held perform data mining optional
optional, not held use markup languages optional

03 information skills 6 required, 4 supplementary

still to learn manage data collection systems required
still to learn conduct literature research required
still to learn execute analytical mathematical calculations required
still to learn handle data samples required
still to learn interpret current data required
still to learn report analysis results required

optional, not held create data models optional
optional, not held conduct qualitative research optional
optional, not held conduct quantitative research optional
optional, not held conduct scholarly research optional

04 arts and humanities 1 required, 1 supplementary

still to learn digital image processing required

optional, not held image formation optional

05 management skills 1 required, 1 supplementary

still to learn define technical requirements required

optional, not held define data quality criteria optional

06 engineering, manufacturing and construction 2 supplementary

optional, not held signal processing optional
optional, not held state estimation optional

2 further areas in the appendix

Table 4

Table 4 · Where to start

The 3 entries a computer vision engineer role is least likely to hire without. The ordering is computed from the skill data, not from what pays.

Each entry opens a course search for that skill. Career Overlap earns nothing from these links.

Appendix

Appendix · The rest of the record

All 6 skills that carry over

Skill Type

already held apply statistical analysis techniques skill
already held computer programming knowledge
already held computer simulation knowledge
already held deliver visual presentation of data skill
already held develop data processing applications skill
already held statistics knowledge

The 2 learning areas not shown above

Skill to pick up Tier

07 communication, collaboration and creativity 1 supplementary

optional, not held design user interface optional

08 natural sciences, mathematics and statistics 1 supplementary

optional, not held mathematical modelling optional

20 supplementary skills, helpful but not required

Skill to pick up Tier

optional, not held cognitive computing optional
optional, not held create data models optional
optional, not held debug software optional
optional, not held define data quality criteria optional
optional, not held design user interface optional
optional, not held perform data mining optional
optional, not held quantum computing optional
optional, not held query languages optional
optional, not held resource description framework query language optional
optional, not held signal processing optional
optional, not held use markup languages optional
optional, not held computer graphics optional
optional, not held conduct qualitative research optional
optional, not held conduct quantitative research optional
optional, not held conduct scholarly research optional
optional, not held deep learning optional
optional, not held digital systems optional
optional, not held image formation optional
optional, not held mathematical modelling optional
optional, not held state estimation optional

19 held skills the computer vision engineer role does not ask for

Skill Type

not needed by the target role ICT networking hardware knowledge
not needed by the target role advise on equipment maintenance skill
not needed by the target role analyse big data skill
not needed by the target role apply information security policies skill
not needed by the target role automotive diagnostic equipment knowledge
not needed by the target role automotive engineering skill
not needed by the target role design sensors skill
not needed by the target role electrical engineering knowledge
not needed by the target role electricity knowledge
not needed by the target role electronics knowledge
not needed by the target role ensure equipment maintenance skill
not needed by the target role gather data skill
not needed by the target role manage data skill
not needed by the target role mathematics knowledge
not needed by the target role model sensor skill
not needed by the target role perform data analysis skill
not needed by the target role predictive maintenance knowledge
not needed by the target role test sensors skill
not needed by the target role use automotive diagnostic equipment skill

21 gaps that are knowledge rather than practice

Knowledge gaps usually close through study. Practical skill gaps usually need something you can point at.

Skill to pick up Tier

still to learn Python (computer programming) required
still to learn digital twin technology required
still to learn integrated development environment software required
still to learn principles of artificial intelligence required
still to learn data engineering required
still to learn data science required
still to learn digital image processing required
still to learn image recognition required
still to learn machine learning required
still to learn scientific computing required
optional, not held cognitive computing optional
optional, not held quantum computing optional
optional, not held query languages optional
optional, not held resource description framework query language optional
optional, not held signal processing optional
optional, not held computer graphics optional
optional, not held deep learning optional
optional, not held digital systems optional
optional, not held image formation optional
optional, not held mathematical modelling optional
optional, not held state estimation optional

Index

Other moves recorded from predictive maintenance expert

Full index of moves from predictive maintenance expert

FAQ

Common questions about this move

Can a predictive maintenance expert become a computer vision engineer?

Yes, and it is a career change move. A predictive maintenance expert already covers 15% of what a computer vision engineer is expected to do: 6 skills carry over, 6 of which the computer vision engineer role treats as required.

What skills does a predictive maintenance expert need to become a computer vision engineer?

26 required skills are missing, plus 20 optional ones. They fall into 8 areas of the ESCO skill hierarchy, led by information and communication technologies (icts). The single most important is Python (computer programming).

How hard is the move from predictive maintenance expert to computer vision engineer?

Its learning distance is 86.6 out of 100, which is the career change band. That accounts for both how much is missing and how specialised those skills are.

Note

How this record was compiled

Both occupations are taken from ESCO, which lists the skills and knowledge each occupation is expected to have and marks every one required or optional. Nothing here is a prediction about hiring, and nothing here knows that a particular employer wants a particular certificate. Treat Table 3 as a starting point for your own research rather than a syllabus. The full method states what these figures can and cannot tell you.